clean up 150914 tutorial

tutorials/GW150914.py

-from __future__ import division
-import matplotlib
-matplotlib.use('AGG')
+from __future__ import division, print_function
 import peyote
-import numpy as np
 
 peyote.utils.setup_logger()
 
@@ -10,33 +7,26 @@ outdir = 'outdir'
 label = 'GW150914'
 time_of_event = 1126259462.422
 
-H1, sampling_frequency, time_duration = peyote.detector.get_inteferometer('H1', time_of_event, version=1)
-L1, sampling_frequency, time_duration = peyote.detector.get_inteferometer('L1', time_of_event, version=1)
-IFOs = [H1, L1]
-
-maximum_posterior_estimates = dict(
-    a_1=0, a_2=0, tilt_1=0, tilt_2=0, phi_12=0, phi_jl=0,
-    luminosity_distance=410., iota=2.97305, phase=1.145,
-    waveform_approximant='IMRPhenomPv2', reference_frequency=50., ra=1.375,
-    dec=-1.2108, geocent_time=time_of_event, psi=2.659, mass_1=36, mass_2=29)
+H1, sampling_frequency, time_duration = peyote.detector.get_inteferometer('H1', time_of_event, version=1, outdir=outdir)
+L1, _, _ = peyote.detector.get_inteferometer('L1', time_of_event, version=1, outdir=outdir)
+interferometers = [H1, L1]
 
 # Define the prior
 prior = dict()
-prior['mass_1'] = peyote.prior.Uniform(10, 80, 'mass_1')
-prior['mass_2'] = peyote.prior.Uniform(10, 80, 'mass_2')
+prior['mass_1'] = peyote.prior.Uniform(30, 50, 'mass_1')
+prior['mass_2'] = peyote.prior.Uniform(20, 40, 'mass_2')
 prior['geocent_time'] = peyote.prior.Uniform(time_of_event-0.1, time_of_event+0.1, name='geocent_time')
+prior['luminosity_distance'] = peyote.prior.PowerLaw(alpha=2, minimum=100, maximum=1000)
 
-# Create the waveformgenerator
-waveformgenerator = peyote.waveform_generator.WaveformGenerator(
-     peyote.source.lal_binary_black_hole, sampling_frequency,
-     time_duration, parameters={'waveform_approximant': 'IMRPhenomPv2', 'reference_frequency': 50})
+# Create the waveform generator
+waveform_generator = peyote.waveform_generator.WaveformGenerator(
+    peyote.source.lal_binary_black_hole, sampling_frequency, time_duration,
+    parameters={'waveform_approximant': 'IMRPhenomPv2', 'reference_frequency': 50})
 
 # Define a likelihood
-likelihood = peyote.likelihood.Likelihood(IFOs, waveformgenerator)
+likelihood = peyote.likelihood.Likelihood(interferometers, waveform_generator)
 
 # Run the sampler
-result = peyote.sampler.run_sampler(
-    likelihood, prior, label='GW150914', sampler='pymultinest',
-    npoints=1024, resume=False, outdir=outdir, use_ratio=True)
-truth = [maximum_posterior_estimates[x] for x in result.search_parameter_keys]
-result.plot_corner(truth=truth)
+result = peyote.sampler.run_sampler(likelihood, prior, sampler='dynesty', outdir=outdir, label='label')
+result.plot_corner()
+print(result)